Traffic lights are no exception. The American traffic lights that have remained essentially unchanged for over a century now, are now affected by machine learning. The result is an efficient and safer transportation world. Technology for preventing traffic signals, for example can assist drivers in avoiding dangerous collisions with pedestrians. A system that combines traffic lights and e-bike/scooter sensor can automatically time stoppages to align with commuters’ daily schedules.
IoT sensors and connectivity technologies allow smarter traffic control systems to maximize energy efficiency by optimizing signal timings in accordance with actual conditions. The data from cameras and sensors can be pre-processed in the device itself or transmitted to the traffic management hub where it is integrated into AI algorithms. The results are more precise modeling and predictive analysis to avoid congestion, coordinate public transportation schedules, and reduce carbon emissions.
These innovative technologies could transform urban transport systems. Smart e-bike/scooter sensor for instance, can detect and communicate the location of personal vehicles shared by others to make ride-sharing more efficient. Micromobility payment systems however permit on-street parking or road tolls with no requirement for accurate change.
IoT smart traffic technology could also improve public transit efficiency, making it easier for commuters to track buses and trams in real time using live tracking apps. Intelligent intersection technology could help prioritize emergency vehicles to ensure they reach their destination faster this is a major breakthrough that has already reduced crash rates in certain cities.
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